A secured optimised AOMDV routing protocol in MANET using lightweight continuous multimodal biometric authentication

被引:2
|
作者
Brindha N.V. [1 ]
Meenakshi V.S. [2 ]
机构
[1] Department of Computer Science, Bharathiar University, Tamilnadu, Coimbatore
[2] PG and Research Department of Computer Science, Chikkanna Government Arts College, Tamilnadu, Tirupur
关键词
Adhoc on-demand multipath distance vector (AOMDV); Biometric identification systems; Flower pollination algorithm (FPA); Mobile ad hoc networks (MANETs); Multimodal biometrics;
D O I
10.1007/s12652-022-03836-7
中图分类号
学科分类号
摘要
Mobile ad hoc networks (MANETs) is a very popular research area due to their wide application and ease of deployment. Due to the inherent nature of MANET and the lack of any centralized security mechanism, it is vulnerable to a number of network security attacks. Sybil attack is one of the security threats that paves the way for many other attacks by hiding the presence of malicious nodes in the network. It also affects the routing performance and security by creating a disturbance in the routing mechanism. The authentication process confirms the genuineness of the user’s identity and further ensures that the resources are accessed by genuine users only. The systems of biometric identification are now becoming very popular and have also been researched widely in recent times. Using a combination of either two or more biometric modalities in a system for verification or identification is an emerging trend. Also, continuous biometric authentication is gaining more importance as the user is monitored for legitimate throughout the session and can report any attacker found. Palmprint and fingerprint are the two biometrics used for authentication in the present work. The ad-hoc on-demand multipath distance vector (AOMDV) based protocol of routing will compute multiple loop-free paths for every route discovery in MANETs. To improve the efficiency of the routing, heuristic methods are applied. In this work, this flower pollination algorithm has been proposed along with the AOMDV and Biometrics for continuous authentication for Sybil attack detection. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
引用
收藏
页码:16115 / 16131
页数:16
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